Skip to main content
Glama
sohumsuthar

ntopology-mcp

by sohumsuthar

add_block

Add a computed block to an nTop notebook by specifying its typed signature, output type, and input block IDs.

Instructions

Add a computed block. Give the full typed signature from search_blocks. Inputs are source block ids in parameter order; use 0 for an unconnected optional input. A list parameter takes exactly one core.list block.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
funcYesTyped signature, e.g. "box_from_corners<point,point>"
nameYes
typeYesOutput type, e.g. "implicit"
inputsYes
outputNo
blockIdNoDefaults to the next free id
notebookYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

A3.5/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are present, so the description carries the full burden. It discloses input behavior (source block ids in order, 0 for unconnected, list parameter requirement) but does not mention side effects, permissions, or return values. It adds some behavioral detail but is not comprehensive.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three concise sentences, front-loaded with the core action. Each sentence adds essential information about signature, input structure, and list handling. No redundancy or wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With 7 parameters, no annotations, and no output schema, the description covers the two most complex parameters (func and inputs) but omits guidance for the other required parameters (name, output, notebook). An agent may struggle to fill all fields correctly, especially since the schema descriptions are sparse.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is only 43%, so the description must compensate. It clarifies the func parameter (typed signature from search_blocks) and the inputs array (order, 0 for optional, list handling). However, it leaves name, output, and notebook unexplained. It partially fills the gap but not fully.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states the action 'Add a computed block' with a clear verb and resource. It implies differentiation from add_literal through the word 'computed' and the specifics about typed signatures and inputs, but does not explicitly name the sibling tool. Overall it is clear about what it does.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It instructs to get the signature from search_blocks, implying a prerequisite step. It explains how to construct inputs (order, 0 for unconnected, list types). However, it does not explicitly state when to prefer this over add_literal or other alternatives, so the usage context is partial.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/sohumsuthar/ntopology-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server